Revised EAAAODV 394 394

8/7/2019 Revised EAAAODV 394 394

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ADAPTIVELINKTIMEOUTWITHENERGYAWAREMECHANISM

FORON-DEMANDROUTINGINMANETS

M.Tamilarasi

1,T.G.Palanivelu

2,

1,2DepartmentofECE,PondicherryEngineeringCollege,Puducherry-605014.

Email:[email protected];

[email protected].

ABSTRACT

MobileAdHocNetworks(MANETs)aremulti-hopwirelessnetworkswhereall

nodes cooperatively maintain network connectivity. When the size of the

networkislargeandthenodesarehighlymobile,thefrequencyoflinkfailure

and energy consumption of the nodes will be more. Link failure will be

identifiedonlyduringthetransmissionofdatapackets.Duetothis,controlload

of the network will increase. To overcome this problem, in this paper, an

innovative algorithm is suggested to remove the stale paths after a certain

timeout period which ismade adaptive by taking hop countof the path into

consideration.Tominimizethepowerconsumptionoftheentirenetwork,inthis

paper,anenergyawareapproachisproposedforon-demandprotocols.Energyawareapproachisatwo-prongedstrategyconsistingofloadbalancingapproach

and transmission power control approach. In this paper, we propose a

mechanism which integrates the adaptive timeout approach, load balancing

approachandtransmitpowercontrolapproachtoimprove theperformanceof

on-demand routing. We applied this integrated mechanism on Ad hoc On-

demandDistanceVector(AODV)routingprotocoltomakeitasEnergyAware

Adaptive AODV (EAA AODV) routing protocol. The performance of EAAAODV is also compared with that of standard AODV with the help of

simulationscarriedoutusingGloMoSimsimulator.Fromsimulationresultsitis

learntthatEAAAODVdecreasesthenumberofcontrolpackets,increasesthe

packetdeliveryratioandreducespowerconsumption.

Keywords:MobileAdHocNetworks(MANETs), Route timeout, energyaware routing, ondemandrouting. 1.INTODUCTION

Mobileadhocnetwork(MANET)isbecoming

increasingly popular as a means of providing

instantnetworking toagroupofpeoplewhomay

not be within the transmission range of one

another. MANET is self-initializing, self-

configuring and self-maintaining. They are

characterized by multi-hop wireless connectivity,

frequentlychangingtopologywhichrequiresefficient

dynamic routingprotocols[1].The routingprotocols

that can be applied for medium size networks are

broadlyclassifiedasproactiveandreactiveprotocols.

Reactiveprotocolsaremorepreferredduetotheiron-

doi:10.1994/s1001002536 UbiCC Journa

UbiCC Journal - Volume 4 Number 4 Page 1157
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demand nature. Route caching is vital in on-

demand routing protocols. In order to reduce

routing overhead by making use of available

informationefficiently,manyresearchworkshaveconcentrated on the link life time and path life

time.JainTangetal[2]haveproposedaheuristic

algorithm for the formation of link duration

predictiontableandtofindapathwithmaximum

duration. RezaShamekh and Nasser Yazdani [3]have used routing table stability prediction

parameter in routing table entry for selecting a

route. Marina and Das [4] have suggested wide

error notification to eliminate stale paths which

requires the maintenance of state information at

intermediate nodes. Wenjing Lou and Yuguang

Fang [5] studied the effect of static lifetime

assignment and received-control packet based

adaptivetimeoutmechanismontheperformanceof

MANET using DSR. Gautam Barua and

ManishAgarwal [6] have proposed a queue

structurewhichactsasaroutecacheinAODV.In

this paper, an adaptive timeout approach is

proposedforassigning a timeoutperiodforevery

cached routebasedon hop countto remove stale

routes.

The failure of a single node in MANET can

greatly affect the network performance. Since

mobile nodesare usuallybattery-operated,oneof

the major reasons of link failure is battery

exhaustion.Inordertomaximizethelife-timeofa

mobile node,it isimportant to reduce the energyconsumptionofanode.Therearemanystrategies

proposed in literatures to minimize the required

active communicationenergy. C.K. Toh[7]has

proposed conditional max-min battery capacity

routing (CMMBCR) to choose a shortest path

amongallpathsinwhicheverynodehasabattery

capacity above a predefined threshold value.

Sheetalkumar Doshi and Timothy X Brown [8]

haveappliedminimum transmitpower controlon

Dynamic Source Routing (DSR) protocol. For

sensor networks, Frederick J. Block and Carl

W.Baum[9]havepresentedasetofroutingmetrics

that utilize an estimate of remaining lifetime ofeach node. Mohammed Tarique et al [10] have

applied transmission power control and load

sharing approach in DSR using the minimum

energytotransmitpowerratioastheparameterfor

selectingaroute.Inourpaper,theloadbalancing

approach is based on available energy at every

nodeandrequiredenergyfortransmittingapacket.

In this paper, we have integrated the adaptive

timeout approach, load balancing approach and

transmitpowercontrolapproachasamechanismto

improve the performance of on-demand routing.

Weapplied this integratedmechanismon AODV

tomakeitasEnergyAwareAdaptiveAODV(EAA

AODV).

The rest of the paper is organized as follows:

Section 2 gives the overview of AODV protocol.Section 3 describes the adaptive link timeout

approach and energy aware approach. Section 4

presents the simulation results and conclusions are

summarizedinSection5.

2.OVERVIEWOFAODVPROTOCOL

In AODV, a source node that wants to send a

messagetoadestination,forwhichitdoesnothavea

route, broadcasts a Route Request (RREQ) packet

across the network.All nodes receiving this packet

update their informationabout thesourcenode.The

RREQcontainsthesourcenodesaddress,broadcast

ID, destination nodes address, current sequencenumber of source node as well as the most recent

sequence number of destination node. Nodes use

these sequence numbers to detect active routes. A

node thatreceivesaRREQcansenda RouteReply

(RREP)ifitiseitherthedestinationorhasarouteto

thedestinationwithasequencenumbergreaterthan

orequaltothesequencenumberthatRREQcontains.

Otherwise, it rebroadcasts the RREQ. Nodes keep

trackoftheRREQsourceaddressandbroadcastID,

discarding any RREQ they have already processed.

As the RREP propagates back to the source, nodes

setupentriestothedestinationintheirroutingtables.

The route is established once the source nodereceives the RREP. This algorithm also includes

route maintenance facilities. For every route in a

routing table, a node maintains a list of precursor

nodes using that route and informs them about

potentiallinkbreakageswithRERRmessages.Each

node also records individual routing table entries

[11].

3.ADAPTIVELINKTIMEOUTWITH

ENERGYAWAREMECHANISM

3.1AdaptiveLinkTimeoutApproach

InMANETs, link failurewill be identified onlyduringthetransmissionofdatapackets.Duetothis,

latencyandcontrolloadofthenetworkisincreased.

On-demandprotocolslikeAODVdonotpossessany

timer basedmechanism to identify the stale routes

residingin routecache. Ifnot cleaned explicitlyby

the error mechanism, stale cache entries will stay

forever inthecache.Cachemay contain routes that

areinvalid.Then,routerepliesmaycarrystaleroutes.

Attempteddatatransmissionsusingstaleroutesincur

overheads, generate additional error packets and

polluteothercacheswhenapacketwithastaleroute

isforwarded.

doi:10.1994/s1001002536 UbiCC Journal



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To overcome this problem, an innovative

approach is suggested to remove the stale paths

after a certain timeout period which is made

adaptive by taking full path into consideration.This approachcan beapplied for any on-demand

routingprotocol and in this paperit isappliedto

AODV.Thealgorithmic form ofthisapproachis

givenbelow.

3.1.1 Algorithm for Adaptive Link Timeout in

AODV

The steps that are performed at theprecursor

node ofa broken link inadative approach are as

follows:

Step1:checkallroutetableentriesfortheforwardpath.

Step 2: If the next hop for any current entry

matcheswiththenextnodeofthebrokenlinkand

ifthecurrententryismarkedactive,gotostep3.

Step3:Markthecurrententryintheroutetableas

inactivated.

Step 4: Get the hop count from the inactivated

entrymentionedinstep3.

Step5:Calculatethenewbadlinklifetimebased

onhopcount.

Step6:Setthecurrenthopcounttoinfinityand

changethecurrentlifetimeaccordingtonewbadlinklifetime.

Step7:SettheAODVtimerwithnewbadlinklife

time.

Asthebad-linklifetimeisassociatedwiththelife

timeoftheparticularroute,reducingthebadlink

lifetime reduces the life time of the route

concerned.

3.2EnergyAwareApproachMobileadhocnetworksarepowerconstrained

asmost ad hoc mobile nodes todayoperatewithlimited batterypower.Hencepowerconsumption

becomes an important issue. It is important to

minimize the power consumption of the entire

networkinordertomaximizethelifetimeofadhoc

networks.Toaccomplishthistoacertainextent,in

thispaper energyaware approach isproposedfor

on-demandprotocols.Energyawareapproachisa

two-prongedstrategywithloadbalancingapproach

and transmission powercontrol approach. Asper

theloadbalancingapproach,on-demandprotocols

select a routeat any time basedon theminimum

energy availability of the routes returned by the

RREPsandtheper-packetenergyconsumptionofthe

route at that time. As per the transmission power

control approach, once a route is selected,

transmission power will be controlled to theminimum required level, on a link by link basis to

reduce thepower consumptionofevery nodein the

selectedpath.

3.2.1LoadbalancingapproachRoute discovery mechanism in EA AODV is

illustratedinFig.1.Node1isthesourceandnode5is

the destination node. Assume that all nodes have

emptycaches.Attimet,whenthesourceinitiatesa

route discovery, the available energy levels of the

nodes and their current required transmit power

levelsareasshowninFigure1.Thesourceinitiatesa

route discovery by broadcasting the RREQ packet.

Node2and node4arewithin thetransmission range

ofnode1.Sinceintermediatenodes2and4arenotthe

destination,thesetwonodesaddtheirownnode-ids

in the RREQ and rebroadcast that RREQ packet.

Once the destination receives the RREQ packet, it

sends a reply to the source by reversing the path

throughwhichitreceivestheRREQpacket.

Figure1.RoutingInEAAODV

Letusassumethatdestinationrepliesbacktothe

source using the route 5321. When the

intermediate node3 receives the RREP packet it

estimates its remaining battery energy using the

available energy ofnodeand the required transmit

powerofapacketatthatnodeandletthisvaluebeX.

Node 3 records this valuein thatRREPpacket and

forwards the RREP to next hop which is node 2.

Node2estimatesitsremainingbatteryenergyinthe

sameway.LetthisvaluebeY.Italsoreadsthevalue

XrecordedintheRREPpacketandcomparesXwith

Y.Node2willreplaceXbyY,onlyifYislessthan

X,orelse,XwillberetainedintheRREP.LetYbe

less thanX.Thus, theRREPcarry the valueof the

minimum remaining battery energy Y of the path

1235. So the source 1 records this path in the

cachealongwithY.Similarly,ifsource1isassumed

todiscoveranotherpath145whichhasminimum

battery energy Z, and if Y is greater than Z, the

1

4 5

32

Eavailable3,Erequired

Source

Destination

Eavailable5,Erequired

Eavailable1Erequired

Eavailable4ErequiredEavailable5,Erequired




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sourcethenselectsthepath1235,becausethis

pathhashigherminimumbatteryenergy thanthe

shortest path 145. Thus, in EA AODV, the

mobile nodes which are very likely to drain outbatteriesareavoidedintheroutediscoveryphase.

Figure 2. Flowchart for selecting the highest

minimumenergyroute

The available energy level and the required

transmit power level of a node are taken into

account while making routing decision. The

subtraction of current availableenergy levels and

the required transmit power levels of nodesindicatehowlikelythesenodeswilldepletebattery

energy. Inorder todo that a source node findsa

minimumenergyrouteEremattimetsuchthatthe

followingcostfunctionismaximized.

C(E,t)=max{Erem}(1)

Erem=Eavailable(t)-Erequired(t)(2)

Where, Erem is the remaining energy of node,

Eavailable(t)istheavailableenergyofnode,Erequired(t)istherequiredtransmitpowerofapacketatnode.

Theenergyrequiredinsendingadatapacketofsize

Dbytesoveragivenlinkcanbemodeledas

E(D)=K 1D+K2(3)

K1=(PtPacket

+Pback)8/BR

K2=((PtMAC

DMAC

+Ptpacket

Dheader

)8/BR)+Eback

Where,Pback

andEbackarethebackgroundpowerand

energy used upin sendingthe datapacket,PtMAC

is

thepoweratwhichtheMACpacketsaretransmitted,

DMAC

isthesizeoftheMACpacketsinbytes,Dheader

isthesize of the trailer and the header of thedata

packet,Ptpacket

isthepoweratwhichthedatapacketis

transmittedand BR is the transmission bit rate [8].

Typical values of K1 and K2 in 802.11 MAC

environmentsat2Mbpsbitrateare4 sperbytesand

42J respectively. Flow chart for load balancing

approachisgiveninFig.2

3.2.2AlgorithmforTransmissionPowerControlApproachStep1:Transmitpowerisrecordedinthedatapacket

byeverynodelyingalongtheroutefromsourceto

destinationanditisforwardedtothenextnode.

Step2:Whenthenextnodereceivesthatdatapacket

atpowerPrecv,itreadsthetransmitpowerPtxfromthe

packet, and recalculates the minimum required

transmitpowerPmin,fortheprecursornode.

Pmin=(Ptx-Precv)+Pthreshold+Pmargin

WherePthresholdistherequiredthresholdpowerofthe

receivingnodeforsuccessfulreceptionofthepacket.The typical value of Pthreshold in LAN 802.11 is

3.65210watt.To overcome the problem of unstable

linksduetochannelfluctuations,amarginPmarginis

included.Because the transmit power ismonitored

packetbypacket,inourwork,wemaintainamargin

of1dB.

Step 3: The recalculated minimum required

transmissionpower,Pminissenttotheprecursornode

throughacknowledgement(ACK).

Step 4: When the ACK packet is received by the

precursor node, it records the modified transmit

powerinthepowertableandtransmitstheremaining

packetswithPmin.

Step 5: When a node can not find a record in the

powertableforaparticularnode,whichwillbethe

casewhentwonodesneverexchangedpacketbefore,

ittransmitswithdefaultpowerlevelof280mW.

In this paper, energy aware approach combines

the load balancing approach and the transmission

powercontrolapproachandisappliedonAODVto

Start

DestinationInitiatesRREP

viadifferentpaths

If(Node==

Sourcenode)

RREQ

Sourcenodewaits

untilthetimer

Comparestheminimumenergy

valuesfromRREPs

SelectsaroutetothedestinationwithMax

{minimumEnergy

Values}

Stop

YES

RemainingEnergy

Erem=Eavilable-Erequired

EpathminErem

Erem


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make it as Energy Aware AODV (EA

AODV).Energy Aware Adaptive AODV (EAA

AODV) integrates the adaptive link timeout

approachandenergyawareapproach.

4.PERFORMANCEEVALUATION

4.1SimulationScenarioThetotalnumberofnodesisfixedas50forthe

simulation. The nodesmoved inside a simulation

areaof(1500300)m.Thesimulationtimeiskept

at900seconds.Thenodesmovewithamaximum

velocity of 20m/s and according to the random

waypoint mobility model. In this model, a node

randomlychoosesaspeedforthenextmovewhich

isuniformlydistributedbetween0andthemaximal

velocity and a point in the simulation area,.

Subsequently,thenodedrivestotheselectedpoint

at constantspeed.Afterarriving at the end point

the node remains there for a certain time.

Subsequently, the node repeats the operation by

selecting a new end point and a new speed. The

simulation is performed for different CBR

connections with a transmitted power of 15-

dBm.This scenario was simulated in GloMoSim

[12] simulator for comparing the performance of

EAAAODVwithAODV.

4.2PerformanceMetrics

Weevaluatefivekeyperformancemetrics:(i)PacketDeliveryRatioistheratioofthenumber

of packets received to the number of packets

transmitted.Thisisanimportantmetricbecauseit

revealsthelossrateseenbythetransportprotocols

and also characterizes the completeness and

correctnessoftheroutingprotocol.

(ii) Routing Overhead is the sum of all

transmissions of routing packets sent during thesimulation. For packets transmitted overmultiple

hops, each transmission over one hop, being

countedasonetransmission.

(iii) End-to-End Delay is the total delay that a

packet experiences as it is traveling through thenetwork.Thisdelayisbuild-upbyseveralsmaller

delaysinthenetwork.

(iv)EnergyConsumptionperpacketistheratioof

the total energy consumed by the nodes in the

network to the number of packets successfully

reachedthedestinations.(v)AverageEnergy Consumptionpernodeisthe

ratiooftotalenergyconsumedbythenodesinthe

networktothetotalnumberofnodespresentinthe

network.

4.3PerformanceComparisonofEAAAODVand

AODVThe three performance metrics listed in section

4.2 namely average energy consumption per node,routingoverheadandpacketdeliveryratiohavebeen

evaluated as a function of traffic connections for

comparingtheperformanceofEAAAODVwiththat

ofAODV.Trafficconnectionreferstothenumberof

source-destination pairs participating in

communication. From Fig. 3 it is observed that

EAAAODV gives 20% less average energy

consumption per node comparedwith the standard

AODV.Thisismainlyattributedtotheenergyaware

approach and the reduction in number of control

packetsduetoadaptivelinktimeoutapproach.

Figure3.AverageEnergyConsumptionpernode

From Fig. 4 it is observed that the number of

controlpacketsgeneratedbyEAAAODVislessthan

thatofAODVinahightrafficscenario.Thiseffectis

due to the reduced congestion in the paths. On an

average,thenumberofcontrolpacketsgeneratedbyEAA AODV is 10% less compared to the basic

AODV. In Fig. 5 we can see that EAA AODV

performs better than the basic AODV with an

averageof3.5%increaseinpacketdeliveryratio.

The other two performance metrics listed in

section 4.2 namely energy consumption per packet

andaverageend-to-enddelayhavebeenevaluatedas

a function of varying terrain dimensions for

comparingtheperformanceofEAAAODVwiththatof AODV. Number of source-destination pairs has

been fixed as 25. FromFig. 6 it is observed that

energy consumption per packet of EAA AODV is

muchlessthanthatofAODVanditisalsoobserved

that per packet energy consumptionofbothAODV

andEAAAODVisincreasingslightlyastheterrain

dimension is increasing. When the area increases,

energy consumption per packet increases, because

packets may travel via many more hops in larger

network area. Fig. 6 is shows that EAA AODV

protocol consumes 25% less energy per packet

comparedtoAODV.




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Figure4.ControlOverhead

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

0 5 10 15 20 25 30

No.ofconnections

Packetdelivery

ratio

EAAAODV

AODV

Figure5.PacketDeliveryRatio

Figure.6EnergyConsumptionperpacket

Fig.7showsthattheaverageend-to-enddelay

experiencedbythepackets ismore inthecaseof

EAA AODV compared to AODV due to theinclusion of extra information such as remaining

battery energy, packet transmission power in the

packet header. Moreover, packets are not always

sentviaminimumhop.Henceaverageend-to-end

delayis52%highinEAAAODVcomparedtothe

basicAODV.

Figure7.AverageEnd-to-EndDelay

Simulation results indicate that the combined

application of link timeout approach and energy

awareapproachonAODVimprovesitsperformanceby reducing the per-node as well as per-packet

energy consumption and by increasing the packet

deliveryratio.

5.CONCLUSION

Inthispaper,anefficientmechanismisproposed

for on demand routing protocols in MANETs to

reducethecontrolpacketloadofthenetworkthrough

removalofstaleroutesandtomaximizethelifetime

of the network by combining the adaptive link

timeout and energy aware approaches. This

mechanism has been applied to AODV. FromsimulationresultsitislearntthatEAAAODVonan

average reduces energy consumption per node by

20% and control packet loadby 10% and increases

the packet delivery ratio by 3.5% compared tostandardAODV.Thepricepaidforthisimprovement

isthe52%increaseinaverageend-to-enddelaydue

to the inclusion of extra information in the packet

header.EAAAODVdecreasesthenumberofcontrol

packets, increases the packet delivery ratio andreducespowerconsumption.

6.REFERENCES

[1] C.E. Perkins and E.M.Royer, Ad HocOn

Demand Distance Vector Routing, in

proceedings of the 2nd IEEE Workshop on

MobileComputingSystemsandApplications,pp.

90-100,February1999.

[2] Jain Tang, Guoliang Xue and Weiyi

Zhang,Reliable Routing in Mobile Ad Hoc

NetworksBased onMobility Prediction, IEEE

Personal Communications, Vol.19, pp.466-474,

March2004.

[3]RezaShamekh,Nasserazdani,Routing table

stabilitypredictioninMobileAdhocNetworks,




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IEEEPersonalCommunication,Vol.17,pp.268-

272,Sep.2005.

[4] MaheshK.MarinaandSamirR.Das,Impactof

Caching and MAC Overheads on RoutingPerformanceinAdHocNetworks,vol.27,issue

3,February2004,Pages239-252.

[5] Wenjing Lou and Yuguang Fang, Predictive

Caching Strategy for On-Demand Routing

Protocols in Wireless Ad Hoc Networks,

WirelessNetworks,Vol.8, pp.671-679, October

2002.

[6].GautamBaruaandManishAgarwal,Caching

ofRoutesinAdhocOn-DemandDistance

Vector(AODV)RoutingforMobileAdhoc

Networks,InternationalConferenceon

ComputerCommunications,November2002[7]. C.K.Toh, Maximum Battery Life Routing to

Support Ubiquitous Mobile Computing in

Wireless Ad Hoc Networks, IEEE

Communications Magazine, pp 138-146, June

2001.

[8].SheetalkumarDoshi,TimothyXBrown,AnOn

DemandMinimumEnergyRoutingProtocolfor

aWireless AdHoc Networks, Proceedings of

ACM SIGMOBILE Mobile Computing and

CommunicationReview,Vol.6,Issue.3,pp.50-

66,July2002.

[9].FrederickJ.Block,CarlW.Baum,Informationfor routing in energy- constrained ad Hoc

networks,AdHocNetworks4(2006),pp499-

08.URL:http://www.elsevier.com/locate/adhoc

[10]Mohammed Tarique, Kemal E. Tepe, and

MohammedNaserian,Energy SavingDynamic

SourceRoutingforAdHocWirelessNetworks,

IEEEinternational ConferenceonModeling

andOptimizationinMobileAdhocandWireless

Networks,pp305-310,December2005.

[11 C.E.Perkins, E.M.Royer, S.R.Das, Ad hoc On-

Demand Distance Vector (AODV) Routing,Internet Draft, draft-ietf-manet-aodv-12.txt, 15,

Nove-mber2002.(Workinprogress).URL:http://www.ietf.org/internet

drafts/draft-ietf-manet-aodv-12.txt

[12]Jorge Nuevo, A Comprehensible GloMoSim

Tutorial, University of Quebec, September

2003.



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